Electrolytic aluminum temperature tank detection method and system, detection robot and storage medium

Abstract

The invention relates to an electrolytic aluminum temperature tank detection method and system, a detection robot and a storage medium. The method comprises the following steps: acquiring related environment data of an electrolytic aluminum temperature tank in real time through a preset sensor, preprocessing the related environment data of the electrolytic aluminum temperature tank to obtain preprocessed related environment data, and performing anomaly recognition on the preprocessed related environment data based on a pre-trained anomaly recognition model to obtain an anomaly recognition result, and feedback is carried out based on the abnormity identification result. Compared with the prior art, according to the embodiment of the invention, long-term stable detection can be carried out in an extreme environment, the safety risk is reduced, related environment data of the electrolytic aluminum temperature tank can be detected in real time, production accidents caused by manual errors are avoided, and the safety coefficient of related detection personnel can be improved.

Description

Technical Field

[0001] The present disclosure relates to the field of automatic detection technology, and in particular to an electrolytic aluminum temperature tank detection method, system, detection robot and storage medium. Background Art

[0002] Aluminum electrolytic cells (temperature cells) play an important role in the aluminum electrolysis industry. In a strong magnetic field and corrosive gas environment, real-time monitoring of the temperature and equipment status in the cell is critical to improving production efficiency and ensuring safety.

[0003] However, the existing manual inspection method is inefficient, has safety risks, and cannot operate stably for a long time in extreme environments. Therefore, there is an urgent need for an automated, intelligent inspection method and system that can operate stably in harsh environments. Summary of the invention

[0004] In order to solve the above technical problems or at least partially solve the above technical problems, the present disclosure provides an electrolytic aluminum temperature tank detection method, system, detection robot and storage medium.

[0005] In a first aspect, an embodiment of the present disclosure provides a method for detecting an electrolytic aluminum temperature tank, the method being applied to a detection robot, the method comprising:

[0006] Obtain relevant environmental data of the electrolytic aluminum temperature tank in real time through preset sensors;

[0007] Preprocessing the relevant environmental data of the aluminum electrolytic temperature tank to obtain the preprocessed relevant environmental data;

[0008] Based on the pre-trained anomaly recognition model, anomaly recognition is performed on the pre-processed related environmental data to obtain an anomaly recognition result, and feedback is provided based on the anomaly recognition result.

[0009] In some embodiments, before obtaining relevant environmental data of the electrolytic aluminum temperature tank in real time through a preset sensor, the method further includes:

[0010] Acquire surrounding environment perception data of the detection robot, perform path planning based on the surrounding environment perception data, and obtain a detection path;

[0011] The detection robot is controlled based on the detection path to complete the detection task.

[0012] In some embodiments, the detection robot adopts an antimagnetic design, and the antimagnetic design includes:

[0013] Select targeted antimagnetic materials and optimize the layout and structure of electronic components to ensure that the inspection robot can operate stably and undisturbed under strong magnetic fields.

[0014] In some embodiments, the inspection robot adopts a corrosion-resistant design, and the corrosion-resistant design includes:

[0015] The shell of the inspection robot is made of highly corrosion-resistant materials and is equipped with a special surface coating to enable the inspection robot to operate stably in an environment with a high concentration of corrosive gases.

[0016] In some embodiments, the real-time acquisition of relevant environmental data of the electrolytic aluminum temperature tank by a preset sensor includes:

[0017] The temperature in the electrolytic aluminum temperature tank is measured by a temperature sensor;

[0018] Detect the concentration of corrosive gas through gas sensors;

[0019] Collect visual information of equipment and environment in the electrolytic aluminum temperature tank through visual sensors;

[0020] The motion state of the detection robot is monitored by a motion sensor.

[0021] In some embodiments, before performing abnormality identification on the preprocessed relevant environmental data based on the pretrained abnormality identification model and obtaining the abnormality identification result, the method further includes:

[0022] A large amount of historical data is used to train the model to obtain a pre-trained anomaly recognition model.

[0023] In some embodiments, the preprocessing of the relevant environmental data of the electrolytic aluminum temperature tank to obtain the preprocessed relevant environmental data includes:

[0024] Perform noise removal based on the relevant environmental data of the aluminum electrolytic temperature tank to obtain first relevant environmental data;

[0025] Data correction is performed based on the first relevant environmental data to obtain preprocessed relevant environmental data.

[0026] In a second aspect, an embodiment of the present disclosure provides an electrolytic aluminum temperature tank detection system, the system is applied to a detection robot, and the system includes:

[0027] An acquisition unit, used for acquiring relevant environmental data of the electrolytic aluminum temperature tank in real time through a preset sensor;

[0028] A preprocessing unit, used for preprocessing the relevant environmental data of the electrolytic aluminum temperature tank to obtain the preprocessed relevant environmental data;

[0029] The abnormality recognition unit is used to perform abnormality recognition on the preprocessed related environmental data based on a pre-trained abnormality recognition model, obtain an abnormality recognition result, and provide feedback based on the abnormality recognition result.

[0030] In a third aspect, an embodiment of the present disclosure provides a detection robot, including:

[0031] Memory;

[0032] Processor; and

[0033] Computer programs;

[0034] The computer program is stored in the memory and is configured to be executed by the processor to implement the method as described in the first aspect.

[0035] In a fourth aspect, an embodiment of the present disclosure provides a computer-readable storage medium having a computer program stored thereon, wherein the computer program is executed by a processor to implement the method as described in the first aspect.

[0036] In a fifth aspect, an embodiment of the present disclosure further provides a computer program product, which includes a computer program or instructions, and when the computer program or instructions are executed by a processor, the method described in the first aspect is implemented.

[0037] The electrolytic aluminum temperature tank detection method, system, detection robot and storage medium provided by the embodiments of the present disclosure obtain relevant environmental data of the electrolytic aluminum temperature tank in real time through a preset sensor, pre-process the relevant environmental data of the electrolytic aluminum temperature tank to obtain the pre-processed relevant environmental data, perform abnormal identification on the pre-processed relevant environmental data based on a pre-trained abnormal identification model, obtain an abnormal identification result, and provide feedback based on the abnormal identification result. Compared with the prior art, the embodiments of the present disclosure can perform long-term stable detection in extreme environments, reduce safety risks, can detect the relevant environmental data of the electrolytic aluminum temperature tank in real time, avoid production accidents caused by human errors, and can improve the safety factor of relevant detection personnel. BRIEF DESCRIPTION OF THE DRAWINGS

[0038] The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate embodiments consistent with the present disclosure and, together with the description, serve to explain the principles of the present disclosure.

[0039] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, for ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative labor.

[0040] Figure 1 A flow chart of a method for detecting an electrolytic aluminum temperature tank provided in an embodiment of the present disclosure;

[0041] Figure 2 A schematic diagram of the overall architecture of the electrolytic aluminum temperature tank detection system provided in an embodiment of the present disclosure;

[0042] Figure 3 A flow chart of a method for detecting an electrolytic aluminum temperature tank provided by another embodiment of the present disclosure;

[0043] Figure 4 A flow chart of a method for detecting an electrolytic aluminum temperature tank provided by another embodiment of the present disclosure;

[0044] Figure 5 A schematic diagram of the structure of the electrolytic aluminum temperature tank detection system provided in an embodiment of the present disclosure;

[0045] Figure 6 A schematic diagram of the structure of a detection device provided in an embodiment of the present disclosure. DETAILED DESCRIPTION

[0046] In order to more clearly understand the above-mentioned objectives, features and advantages of the present disclosure, the scheme of the present disclosure will be further described below. It should be noted that the embodiments of the present disclosure and the features in the embodiments can be combined with each other without conflict.

[0047] In the following description, many specific details are set forth to facilitate a full understanding of the present disclosure, but the present disclosure may also be implemented in other ways different from those described herein; it is obvious that the embodiments in the specification are only part of the embodiments of the present disclosure, rather than all of the embodiments.

[0048] Aluminum electrolytic cells (temperature cells) play an important role in the aluminum electrolysis industry. In a strong magnetic field and corrosive gas environment, real-time monitoring of the temperature and equipment status in the cell is critical to improving production efficiency and ensuring safety.

[0049] However, the existing manual inspection method is inefficient, has safety risks, and cannot operate stably for a long time in extreme environments. Therefore, there is an urgent need for an automated, intelligent inspection method and system that can operate stably in harsh environments.

[0050] To address this problem, an embodiment of the present disclosure provides a method for detecting an electrolytic aluminum temperature tank, which is described below in conjunction with specific embodiments.

[0051] Figure 1A flow chart of the electrolytic aluminum temperature tank detection method provided in the embodiment of the present disclosure. The executor of the method is a detection device, which can specifically be a detection robot. The method can be applied to the scenario of detecting the electrolytic aluminum temperature tank, and can also be applied to the scenario of automatic detection in a strong magnetic field and corrosive gas environment. It can perform long-term stable detection in extreme environments to reduce safety risks. It can detect the relevant environmental data of the electrolytic aluminum temperature tank in real time to avoid production accidents caused by human errors, and can improve the safety factor of relevant detection personnel. It can be understood that the electrolytic aluminum temperature tank detection method provided in the embodiment of the present disclosure can also be applied in other scenarios.

[0052] Below Figure 1 The electrolytic aluminum temperature tank detection method shown in the figure is introduced. The method is applied to the detection robot. The specific steps of the method are as follows:

[0053] S101. Obtain relevant environmental data of the electrolytic aluminum temperature tank in real time through preset sensors.

[0054] In this step, the detection robot will obtain relevant environmental data of the electrolytic aluminum temperature tank in real time through the preset sensors. Figure 2 As shown, the relevant environmental data of the electrolytic aluminum temperature tank is collected in real time through the data acquisition module. Optionally, the relevant environmental data of the electrolytic aluminum temperature tank may include but are not limited to temperature data, gas concentration, visual image data, and detection robot wheel motion data. In some embodiments, the preset sensors include but are not limited to temperature sensors, gas sensors, visual sensors, and motion sensors.

[0055] Optionally, the temperature sensor is used to accurately measure the temperature in the electrolytic aluminum temperature tank; the gas sensor is used to detect the concentration of corrosive gases; the visual sensor is used to obtain visual information of the equipment and environment in the tank; and the motion sensor is used to monitor the motion state of the detection robot itself. Each sensor works together through an intelligent algorithm, and the multi-sensor data is fused and processed through the intelligent algorithm, and various data information is comprehensively analyzed to improve the accuracy and reliability of the detection results.

[0056] In some embodiments, the detection robot adopts an anti-magnetic design, which includes: selecting target anti-magnetic materials and optimizing the layout and structure of electronic components so that the detection robot can operate stably and undisturbed under strong magnetic fields.

[0057] For example, select materials with good anti-magnetic properties, such as specific alloy materials, for the manufacture of key components of the detection robot to reduce the impact of the magnetic field on the detection robot; reasonably arrange electronic components to avoid magnetic field interference with electronic signal transmission and ensure the normal operation of electronic components; optimize the overall structural design of the detection robot to reduce the induced current of the magnetic field on the structure of the detection robot and ensure the stable operation of the detection robot under strong magnetic fields.

[0058] In some embodiments, the detection robot adopts a corrosion-resistant design, which includes: using highly corrosion-resistant materials to manufacture the detection robot's shell and equipping it with a special surface coating to enable the detection robot to operate stably in an environment with a high concentration of corrosive gases.

[0059] For example, highly corrosion-resistant materials, such as special plastics or alloys, are selected to make the detection robot shell to resist the erosion of corrosive gases; a special surface coating is applied to the outer layer to further enhance the corrosion resistance of the shell and extend the service life of the robot in corrosive environments.

[0060] S102, preprocessing the relevant environmental data of the electrolytic aluminum temperature tank to obtain preprocessed relevant environmental data.

[0061] In this step, after obtaining the relevant environmental data of the electrolytic aluminum temperature tank, the detection robot will pre-process the relevant environmental data of the electrolytic aluminum temperature tank to obtain the pre-processed relevant environmental data. Figure 2 As shown, the data collected by the sensor is processed and analyzed in real time through the real-time data processing and analysis module, and the data processing process is optimized by using intelligent algorithms to improve the accuracy and real-time performance of detection. Preprocessing can include abnormal data correction, and there is no specific limitation on the processing method.

[0062] S103: performing anomaly recognition on the preprocessed relevant environmental data based on a pre-trained anomaly recognition model to obtain an anomaly recognition result, and providing feedback based on the anomaly recognition result.

[0063] In this step, the detection robot is pre-trained with an anomaly recognition model, and the pre-trained anomaly recognition model can be used to perform anomaly recognition on the pre-processed related environmental data to obtain an anomaly recognition result, and feedback is provided based on the anomaly recognition result. By using a machine learning algorithm model to perform anomaly recognition on the data collected by the preset sensor, automatic anomaly detection is achieved, and the machine learning algorithm continuously learns and adapts to environmental changes, continuously optimizes the anomaly recognition model based on new data, and improves the sensitivity and accuracy of detection.

[0064] In some embodiments, the detection strategy can also be adjusted according to environmental changes, such as optimizing sensor measurement parameters when the magnetic field strength changes to prevent false detection, with adaptive capabilities, and applicable to various detection scenarios. Optionally, the detection strategy can also be adjusted according to preset rules, such as increasing the detection frequency of abnormal areas or starting backup sensors for more detailed detection.

[0065] The disclosed embodiment obtains relevant environmental data of the electrolytic aluminum temperature tank in real time through a preset sensor, pre-processes the relevant environmental data of the electrolytic aluminum temperature tank to obtain the pre-processed relevant environmental data, performs abnormal identification on the pre-processed relevant environmental data based on a pre-trained abnormal identification model, obtains an abnormal identification result, and provides feedback based on the abnormal identification result. Compared with the prior art, the disclosed embodiment can perform long-term stable detection in extreme environments, reduce safety risks, detect the relevant environmental data of the electrolytic aluminum temperature tank in real time, avoid production accidents caused by human errors, and improve the safety factor of relevant detection personnel.

[0066] Figure 3 A flow chart of a method for detecting an electrolytic aluminum temperature tank provided by another embodiment of the present disclosure is shown in FIG. Figure 3 As shown, the method includes the following steps:

[0067] S201. Acquire surrounding environment perception data of the detection robot, perform path planning based on the surrounding environment perception data, and obtain a detection path.

[0068] In this step, the surrounding environment perception data of the detection robot can be obtained, and further, path planning is performed based on the surrounding environment perception data to obtain a detection path. Figure 2 As shown in the figure, the inspection robot is equipped with an autonomous navigation system. The autonomous navigation system uses sensors such as laser radar and visual cameras to perceive the environment, plan safe paths, and avoid obstacles in complex environments. The autonomous navigation system combines map construction and path planning algorithms to update the environment map in real time and dynamically plan the optimal path based on task requirements and environmental changes.

[0069] Optionally, the inspection robot also has a remote control system, which transmits the data collected by the inspection robot to the cloud platform through the wireless communication module. The operator can remotely monitor the operating status of the inspection robot and remotely control it as needed. The remote control system has reliable wireless communication technology to ensure the stability and timeliness of data transmission, and provides a convenient user interface for operators to remotely monitor and control the robot.

[0070] S202: Control the inspection robot to complete the inspection task based on the inspection path.

[0071] In this step, after the detection path is obtained, the detection task can be completed according to the planned detection path. In some embodiments, remote control and data transmission can also be achieved through wireless communication and cloud platform to achieve high intelligence and remote monitoring.

[0072] S203, obtaining relevant environmental data of the electrolytic aluminum temperature tank in real time through preset sensors.

[0073] Specifically, the implementation process and principle of S203 and S101 are the same, and will not be repeated here.

[0074] S204, preprocessing the relevant environmental data of the electrolytic aluminum temperature tank to obtain preprocessed relevant environmental data.

[0075] Specifically, the implementation process and principle of S204 and S102 are the same, and will not be repeated here.

[0076] S205. Use a large amount of historical data to train the model to obtain a pre-trained anomaly recognition model.

[0077] In this step, a large amount of historical data can be used to train the model to obtain a pre-trained anomaly recognition model, and the anomaly recognition model can further identify abnormal situations and provide timely feedback, and adaptively adjust the detection strategy according to environmental changes. Historical data refers to the relevant environmental data of the electrolytic aluminum temperature tank collected in the past period of time. Using a large amount of historical data to train the model can enable the anomaly recognition model to identify abnormal situations such as abnormal temperature rise, gas leakage, etc. based on real-time sensor data, and provide timely feedback.

[0078] S206: Perform anomaly recognition on the preprocessed related environmental data based on the pre-trained anomaly recognition model to obtain anomaly recognition results, and provide feedback based on the anomaly recognition results.

[0079] Specifically, the implementation process and principle of S206 and S103 are the same, and will not be repeated here.

[0080] The disclosed embodiment obtains the surrounding environment perception data of the detection robot, performs path planning based on the surrounding environment perception data, obtains the detection path, and controls the detection robot to complete the detection task based on the detection path. Furthermore, the relevant environmental data of the electrolytic aluminum temperature tank is obtained in real time through a preset sensor, and the relevant environmental data of the electrolytic aluminum temperature tank is preprocessed to obtain the preprocessed relevant environmental data. Then, a large amount of historical data is used to train the model to obtain a pre-trained abnormality recognition model, and the pre-processed relevant environmental data is subjected to abnormal recognition based on the pre-trained abnormality recognition model to obtain abnormality recognition results, and feedback is provided based on the abnormality recognition results. Through this method, the detection path can be planned, long-term and stable detection can be performed in extreme environments, safety risks can be reduced, the relevant environmental data of the electrolytic aluminum temperature tank can be detected in real time, production accidents caused by human errors can be avoided, and the safety factor of relevant detection personnel can be improved.

[0081] Figure 4 A flow chart of a method for detecting an electrolytic aluminum temperature tank provided by another embodiment of the present disclosure is shown in FIG. Figure 4 As shown, the method includes the following steps:

[0082] S301. Measure the temperature in the electrolytic aluminum temperature tank through a temperature sensor.

[0083] In this step, the temperature in the electrolytic aluminum temperature tank is measured by a temperature sensor.

[0084] S302, detecting the concentration of corrosive gas through a gas sensor.

[0085] In this step, the concentration of corrosive gas is detected by a gas sensor.

[0086] S303. Collect visual information of equipment and environment in the electrolytic aluminum temperature tank through visual sensors.

[0087] In this step, image data of the equipment and environment in the electrolytic aluminum temperature tank is collected by a visual sensor such as an image acquisition sensor.

[0088] S304: Monitor the motion state of the detection robot through a motion sensor.

[0089] In this step, the motion state of the detection robot is monitored by a motion sensor such as a wheel motion sensor.

[0090] S305. Remove noise based on the relevant environmental data of the electrolytic aluminum temperature tank to obtain first relevant environmental data.

[0091] In this step, the detection robot can remove noise from the relevant environmental data of the electrolytic aluminum temperature tank to obtain first relevant environmental data. The first relevant environmental data is the relevant environmental data after noise removal.

[0092] S306: Perform data correction based on the first relevant environmental data to obtain pre-processed relevant environmental data.

[0093] In this step, the detection robot can perform data correction on the first relevant environmental data to obtain pre-processed relevant environmental data. Specifically, the first relevant environmental data can be subjected to deviation data identification, and the identified deviation data can be corrected to obtain pre-processed relevant environmental data, thereby improving the accuracy of the data and further improving the accuracy and real-time performance of the detection.

[0094] S307: Perform anomaly recognition on the preprocessed related environmental data based on the pre-trained anomaly recognition model to obtain anomaly recognition results, and provide feedback based on the anomaly recognition results.

[0095] Specifically, the implementation process and principle of S307 and S103 are the same, and will not be repeated here.

[0096] The disclosed embodiment measures the temperature in the electrolytic aluminum temperature tank through a temperature sensor, detects the concentration of corrosive gases through a gas sensor, collects visual information of the equipment and environment in the electrolytic aluminum temperature tank through a visual sensor, and monitors the motion state of the detection robot through a motion sensor. Furthermore, noise is removed based on the relevant environmental data of the electrolytic aluminum temperature tank to obtain first relevant environmental data, and data correction is performed based on the first relevant environmental data to obtain pre-processed relevant environmental data. Then, based on the pre-trained abnormality recognition model, abnormality recognition is performed on the pre-processed relevant environmental data to obtain abnormality recognition results, and feedback is provided based on the abnormality recognition results. Through this method, long-term stable detection can be performed in extreme environments to reduce safety risks, and the relevant environmental data of the electrolytic aluminum temperature tank can be detected in real time to avoid production accidents caused by human errors, and the safety factor of relevant detection personnel can be improved.

[0097] Figure 5 The schematic diagram of the structure of the electrolytic aluminum temperature tank detection system provided in the embodiment of the present disclosure. The electrolytic aluminum temperature tank detection system can be the detection robot described in the above embodiment, or the electrolytic aluminum temperature tank detection system can be a component or assembly in the detection robot. The electrolytic aluminum temperature tank detection system provided in the embodiment of the present disclosure can execute the processing flow provided in the electrolytic aluminum temperature tank detection method embodiment, such as Figure 5As shown, the electrolytic aluminum temperature tank detection system 40 includes: an acquisition unit 41, a preprocessing unit 42, and an abnormality recognition unit 43; wherein the acquisition unit 41 is used to acquire relevant environmental data of the electrolytic aluminum temperature tank in real time through a preset sensor; the preprocessing unit 42 is used to preprocess the relevant environmental data of the electrolytic aluminum temperature tank to obtain preprocessed relevant environmental data; the abnormality recognition unit 43 is used to perform abnormality recognition on the preprocessed relevant environmental data based on a pre-trained abnormality recognition model, obtain an abnormality recognition result, and provide feedback based on the abnormality recognition result.

[0098] Optionally, before obtaining the relevant environmental data of the electrolytic aluminum temperature tank in real time through a preset sensor, the system 40 also includes: a planning unit 44 and a control unit 45; the planning unit 44 is used to obtain the surrounding environment perception data of the detection robot, and perform path planning based on the surrounding environment perception data to obtain a detection path; the control unit 45 is used to control the detection robot to complete the detection task based on the detection path.

[0099] Optionally, the detection robot adopts an anti-magnetic design, which includes: selecting target anti-magnetic materials and optimizing the layout and structure of electronic components so that the detection robot can operate stably and undisturbed under a strong magnetic field.

[0100] Optionally, the detection robot adopts a corrosion-resistant design, which includes: using highly corrosion-resistant materials to manufacture the detection robot's shell and equipping it with a special surface coating to enable the detection robot to operate stably in an environment with a high concentration of corrosive gases.

[0101] Optionally, when the acquisition unit 41 acquires relevant environmental data of the electrolytic aluminum temperature tank in real time through a preset sensor, it is specifically used for: measuring the temperature inside the electrolytic aluminum temperature tank through a temperature sensor; detecting the concentration of corrosive gases through a gas sensor; collecting visual information of equipment and environment in the electrolytic aluminum temperature tank through a visual sensor; and monitoring the motion state of the detection robot through a motion sensor.

[0102] Optionally, before performing anomaly identification on the preprocessed related environmental data based on the pretrained anomaly identification model and obtaining an anomaly identification result, the system 40 also includes: a training unit 46; the training unit 46 is used to train the model using a large amount of historical data to obtain a pretrained anomaly identification model.

[0103] Optionally, when the preprocessing unit 42 preprocesses the relevant environmental data of the electrolytic aluminum temperature tank to obtain the preprocessed relevant environmental data, it is specifically used to: remove noise based on the relevant environmental data of the electrolytic aluminum temperature tank to obtain first relevant environmental data; perform data correction based on the first relevant environmental data to obtain preprocessed relevant environmental data.

[0104] Figure 5 The electrolytic aluminum temperature tank detection system of the illustrated embodiment can be used to implement the technical solution of the above-mentioned method embodiment. Its implementation principle and technical effect are similar and will not be repeated here.

[0105] Figure 6 This is a schematic diagram of the structure of a detection device in an embodiment of the present disclosure. The detection device may be a detection robot. Figure 6 , which shows a schematic structural diagram of a detection device 600 suitable for implementing the embodiment of the present disclosure. Figure 6 The detection device shown is only an example and should not bring any limitation to the functions and scope of use of the embodiments of the present disclosure.

[0106] like Figure 6 As shown, the detection device 600 may include a processing device (e.g., a central processing unit, a graphics processing unit, etc.) 601, which can perform various appropriate actions and processes according to a program stored in a read-only memory (ROM) 602 or a program loaded from a storage device 608 to a random access memory (RAM) 603 to implement the electrolytic aluminum temperature tank detection method of the embodiment described in the present disclosure. In RAM 603, various programs and data required for the operation of the detection device 600 are also stored. The processing device 601, ROM 602, and RAM 603 are connected to each other via a bus 604. An input / output (I / O) interface 605 is also connected to the bus 604.

[0107] Typically, the following devices may be connected to the I / O interface 605: input devices 606 including, for example, a touch screen, a touch pad, a keyboard, a mouse, a camera, a microphone, an accelerometer, a gyroscope, etc.; output devices 607 including, for example, a liquid crystal display (LCD), a speaker, a vibrator, etc.; storage devices 608 including, for example, a magnetic tape, a hard disk, etc.; and communication devices 609. The communication devices 609 may allow the detection device 600 to communicate with other devices wirelessly or by wire to exchange data. Although Figure 6 The detection device 600 is shown with various devices, but it should be understood that it is not required to implement or have all the devices shown. More or fewer devices may be implemented or have instead.

[0108] In particular, according to an embodiment of the present disclosure, the process described above with reference to the flowchart can be implemented as a computer software program. For example, an embodiment of the present disclosure includes a computer program product, which includes a computer program carried on a non-transitory computer-readable medium, and the computer program contains a program code for executing the method shown in the flowchart, thereby implementing the electrolytic aluminum temperature tank detection method as described above. In such an embodiment, the computer program can be downloaded and installed from the network through the communication device 609, or installed from the storage device 608, or installed from the ROM 602. When the computer program is executed by the processing device 601, the above functions defined in the method of the embodiment of the present disclosure are executed.

[0109] It should be noted that the computer-readable medium disclosed above may be a computer-readable signal medium or a computer-readable storage medium or any combination of the above two. The computer-readable storage medium may be, for example, but not limited to, an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, device or device, or any combination of the above. More specific examples of computer-readable storage media may include, but are not limited to: an electrical connection with one or more wires, a portable computer disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the above. In the present disclosure, a computer-readable storage medium may be any tangible medium containing or storing a program that may be used by or in combination with an instruction execution system, device or device. In the present disclosure, a computer-readable signal medium may include a data signal propagated in a baseband or as part of a carrier wave, in which a computer-readable program code is carried. This propagated data signal may take a variety of forms, including but not limited to an electromagnetic signal, an optical signal, or any suitable combination of the above. The computer readable signal medium may also be any computer readable medium other than a computer readable storage medium, which may send, propagate or transmit a program for use by or in conjunction with an instruction execution system, apparatus or device. The program code contained on the computer readable medium may be transmitted using any suitable medium, including but not limited to: wires, optical cables, RF (radio frequency), etc., or any suitable combination of the above.

[0110] In some embodiments, the client and the server may communicate using any currently known or future developed network protocol such as HTTP (HyperText Transfer Protocol), and may be interconnected with any form or medium of digital data communication (e.g., a communication network). Examples of communication networks include a local area network ("LAN"), a wide area network ("WAN"), an internet (e.g., the Internet), and a peer-to-peer network (e.g., an ad hoc peer-to-peer network), as well as any currently known or future developed network.

[0111] The computer-readable medium may be included in the detection device, or may exist independently without being assembled into the detection device.

[0112] The computer-readable medium carries one or more programs. When the one or more programs are executed by the detection device, the detection device:

[0113] Obtain relevant environmental data of the electrolytic aluminum temperature tank in real time through preset sensors;

[0114] Preprocessing the relevant environmental data of the aluminum electrolytic temperature tank to obtain the preprocessed relevant environmental data;

[0115] Based on the pre-trained anomaly recognition model, anomaly recognition is performed on the pre-processed related environmental data to obtain an anomaly recognition result, and feedback is provided based on the anomaly recognition result.

[0116] Optionally, when the above one or more programs are executed by the detection device, the detection device may also execute other steps described in the above embodiments.

[0117] Computer program code for performing the operations of the present disclosure may be written in one or more programming languages ​​or a combination thereof, including, but not limited to, object-oriented programming languages, such as Java, Smalltalk, C++, and conventional procedural programming languages, such as "C" or similar programming languages. The program code may be executed entirely on the user's computer, partially on the user's computer, as a separate software package, partially on the user's computer and partially on a remote computer, or entirely on a remote computer or server. In cases involving a remote computer, the remote computer may be connected to the user's computer through any type of network, including a local area network (LAN) or a wide area network (WAN), or may be connected to an external computer (e.g., through the Internet using an Internet service provider).

[0118] The flow chart and block diagram in the accompanying drawings illustrate the possible architecture, function and operation of the system, method and computer program product according to various embodiments of the present disclosure. In this regard, each square box in the flow chart or block diagram can represent a module, a program segment or a part of a code, and the module, the program segment or a part of the code contains one or more executable instructions for realizing the specified logical function. It should also be noted that in some implementations as replacements, the functions marked in the square box can also occur in a sequence different from that marked in the accompanying drawings. For example, two square boxes represented in succession can actually be executed substantially in parallel, and they can sometimes be executed in the opposite order, depending on the functions involved. It should also be noted that each square box in the block diagram and / or flow chart, and the combination of the square boxes in the block diagram and / or flow chart can be implemented with a dedicated hardware-based system that performs a specified function or operation, or can be implemented with a combination of dedicated hardware and computer instructions.

[0119] The units involved in the embodiments described in the present disclosure may be implemented by software or hardware, wherein the name of a unit does not, in some cases, constitute a limitation on the unit itself.

[0120] The functions described above herein may be performed at least in part by one or more hardware logic components. For example, without limitation, exemplary types of hardware logic components that may be used include: field programmable gate arrays (FPGAs), application specific integrated circuits (ASICs), application specific standard products (ASSPs), systems on chips (SOCs), complex programmable logic devices (CPLDs), and the like.

[0121] In the context of the present disclosure, a machine-readable medium may be a tangible medium that may contain or store a program for use by or in conjunction with an instruction execution system, device, or equipment. A machine-readable medium may be a machine-readable signal medium or a machine-readable storage medium. A machine-readable medium may include, but is not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, device, or equipment, or any suitable combination of the foregoing. A more specific example of a machine-readable storage medium may include an electrical connection based on one or more lines, a portable computer disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing.

[0122] The above description is only a preferred embodiment of the present disclosure and an explanation of the technical principles used. Those skilled in the art should understand that the scope of disclosure involved in the present disclosure is not limited to the technical solutions formed by a specific combination of the above technical features, but should also cover other technical solutions formed by any combination of the above technical features or their equivalent features without departing from the above disclosed concept. For example, the above features are replaced with the technical features with similar functions disclosed in the present disclosure (but not limited to) by each other to form a technical solution.

[0123] In addition, although each operation is described in a specific order, this should not be understood as requiring these operations to be performed in the specific order shown or in a sequential order. Under certain circumstances, multitasking and parallel processing may be advantageous. Similarly, although some specific implementation details are included in the above discussion, these should not be interpreted as limiting the scope of the present disclosure. Some features described in the context of a separate embodiment can also be implemented in a single embodiment in combination. On the contrary, the various features described in the context of a single embodiment can also be implemented in multiple embodiments individually or in any suitable sub-combination mode.

[0124] Although the subject matter has been described in language specific to structural features and / or methodological logical actions, it should be understood that the subject matter defined in the appended claims is not necessarily limited to the specific features or actions described above. On the contrary, the specific features and actions described above are merely example forms of implementing the claims.

Claims

1. A method for detecting an electrolytic aluminum temperature tank, characterized in that: The method is applied to detecting a robot, and the method comprises: Obtain relevant environmental data of the electrolytic aluminum temperature tank in real time through preset sensors; Preprocessing the relevant environmental data of the aluminum electrolytic temperature tank to obtain the preprocessed relevant environmental data; Based on the pre-trained anomaly recognition model, anomaly recognition is performed on the pre-processed related environmental data to obtain an anomaly recognition result, and feedback is provided based on the anomaly recognition result.

2. The method according to claim 1, characterized in that Before obtaining relevant environmental data of the electrolytic aluminum temperature tank in real time through a preset sensor, the method further includes: Acquire surrounding environment perception data of the detection robot, perform path planning based on the surrounding environment perception data, and obtain a detection path; The detection robot is controlled based on the detection path to complete the detection task.

3. The method according to claim 1, characterized in that The detection robot adopts an antimagnetic design, and the antimagnetic design includes: Select targeted antimagnetic materials and optimize the layout and structure of electronic components to ensure that the inspection robot can operate stably and undisturbed under strong magnetic fields.

4. The method according to claim 1, characterized in that: The detection robot adopts a corrosion-resistant design, and the corrosion-resistant design includes: The shell of the inspection robot is made of highly corrosion-resistant materials and is equipped with a special surface coating to enable the inspection robot to operate stably in an environment with a high concentration of corrosive gases.

5. The method according to claim 1, characterized in that The real-time acquisition of relevant environmental data of the electrolytic aluminum temperature tank by the preset sensor includes: The temperature in the electrolytic aluminum temperature tank is measured by a temperature sensor; Detect the concentration of corrosive gas through gas sensors; Collect visual information of equipment and environment in the electrolytic aluminum temperature tank through visual sensors; The motion state of the detection robot is monitored by a motion sensor.

6. The method according to claim 1, characterized in that Before performing abnormality recognition on the preprocessed relevant environmental data based on the pre-trained abnormality recognition model to obtain an abnormality recognition result, the method further includes: A large amount of historical data is used to train the model to obtain a pre-trained anomaly recognition model.

7. The method according to claim 1, characterized in that The preprocessing of the relevant environmental data of the electrolytic aluminum temperature tank to obtain the preprocessed relevant environmental data includes: Perform noise removal based on the relevant environmental data of the aluminum electrolytic temperature tank to obtain first relevant environmental data; Data correction is performed based on the first relevant environmental data to obtain preprocessed relevant environmental data.

8. An electrolytic aluminum temperature tank detection system, characterized in that: The system is applied to detect robots, and the system comprises: An acquisition unit, used for acquiring relevant environmental data of the electrolytic aluminum temperature tank in real time through a preset sensor; A preprocessing unit, used for preprocessing the relevant environmental data of the electrolytic aluminum temperature tank to obtain the preprocessed relevant environmental data; The abnormality recognition unit is used to perform abnormality recognition on the preprocessed related environmental data based on a pre-trained abnormality recognition model, obtain an abnormality recognition result, and provide feedback based on the abnormality recognition result.

9. A detection robot, characterized in that: include: Memory; processor; as well as Computer programs; The computer program is stored in the memory and is configured to be executed by the processor to implement the method according to any one of claims 1 to 7.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the method according to any one of claims 1 to 7 is implemented.

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